Scientific workflows: Past,present and future |
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| Affiliation: | 1. University of Edinburgh, School of Informatics, Edinburgh EH8 9AB, UK;2. University of Notre Dame, Center for Research Computing, Notre Dame, IN 46556, USA;3. Université Côte d’Azur, CNRS, I3S, Sophia Antipolis, France;4. Cardiff University, School of Computer Science & Informatics, 5 The Parade, Cardiff CF24 3AA, UK;1. Earth and Climate Cluster, Faculty of Earth and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands;2. Laboratoire des Sciences du Climat et de l''Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France;3. INSTAAR and Department of Geological Sciences, University of Colorado, Boulder, CO 80309, USA;4. Department of Geological Sciences, University of Colorado, Boulder, CO 80309, USA;1. Université de Nice Sophia Antipolis / CNRS UMR7271 I3S, MODALIS team, Sophia Antipolis, France;2. Université de Rennes 1 / INSERM U1099 LTSI, Rennes, France;3. Université de Haute-Alsace, MIPS (EA 2332), Mulhouse, France;4. Université de Lyon 1 / CNRS UMR5220 / INSERM U1044 / INSA-Lyon CREATIS, Lyon, France;5. McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Canada;1. University of Waterloo, Canada;2. Google Inc., United States;3. University of British Columbia, Canada;4. NetApp Inc., Canada;1. ETH Zurich, Switzerland;2. ITMO University, Russia;3. University of Amsterdam, Netherlands;4. VU University Amsterdam, Netherlands;1. University of Manchester, School of Computer Science, Oxford Rd, Manchester M13 9PL, United Kingdom;2. Université Paris Dauphine, Place du Maréchal de Lattre de Tassigny, 75016 Paris, France |
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| Abstract: | This special issue and our editorial celebrate 10 years of progress with data-intensive or scientific workflows. There have been very substantial advances in the representation of workflows and in the engineering of workflow management systems (WMS). The creation and refinement stages are now well supported, with a significant improvement in usability. Improved abstraction supports cross-fertilisation between different workflow communities and consistent interpretation as WMS evolve. Through such re-engineering the WMS deliver much improved performance, significantly increased scale and sophisticated reliability mechanisms. Further improvement is anticipated from substantial advances in optimisation. We invited papers from those who have delivered these advances and selected 14 to represent today’s achievements and representative plans for future progress. This editorial introduces those contributions with an overview and categorisation of the papers. Furthermore, it elucidates responses from a survey of major workflow systems, which provides evidence of substantial progress and a structured index of related papers. We conclude with suggestions on areas where further research and development is needed and offer a vision of future research directions. |
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| Keywords: | Scientific workflows Scientific methods Optimisation Performance Usability |
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